A Virtual Sensor for Predicting Diesel Engine Emissions from Cylinder Pressure Data

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceeding

Abstract

Cylinder pressure sensors provide detailed information on the diesel engine combustion process. This paper presents a method to use cylinder-pressure data for prediction of engine emissions by exploiting data-mining techniques. The proposed method uses principal component analysis to reduce the dimension of the cylinder-pressure data, and a neural network to model the nonlinear relationship between the cylinder pressure and emissions. An algorithm is presented for training the neural network to predict cylinder-individual emissions even though the training data only provides cylinder-averaged target data. The algorithm was applied to an experimental data set from a six-cylinder heavy-duty engine, and it is verified that trends in emissions during transient engine operation are captured successfully by the model.

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Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Reglerteknik
Originalspråkengelska
Titel på värdpublikation2012 IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling
FörlagIFAC
Sidor424-431
ISBN (tryckt)978-3-902823-16-8
StatusPublished - 2012
PublikationskategoriForskning
Peer review utfördJa
Evenemang2012 IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling (E-COSM'12) - Rueil-Malmaison, Frankrike
Varaktighet: 2012 okt 232012 okt 25

Publikationsserier

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ISSN (tryckt)1474-6670

Konferens

Konferens2012 IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling (E-COSM'12)
LandFrankrike
OrtRueil-Malmaison
Period2012/10/232012/10/25

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